Likelihood of recieving a funding if you apply for it.

# Load your data
df <- read.csv("YEAR-04-DATA-PUF.csv")

# List of the base variable names (without _Seek or _Rcv)
funding_types <- c("FndRaise_LocGvtGrnt",
                   "FndRaise_StateGvtGrnt",
                   "FndRaise_FedGvtGrnt",
                   "FndRaise_LocGvtCntrct",
                   "FndRaise_StateGvtCntrct",
                   "FndRaise_FedGvtCntrct",
                   "FndRaise_PFGrnt",
                   "FndRaise_CFGrnt",
                   "FndRaise_DAF",
                   "FndRaise_Corp_Found_Grnt",
                   "FndRaise_UntdWy",
                   "FndRaise_CombFedCmpgn",
                   "FndRaise_OthrGvngPrgrm")

# Calculate success rate for each funding type
success_rates <- sapply(funding_types, function(base) {
  seek_var <- paste0(base, "_Seek")
  rcv_var <- paste0(base, "_Rcv")
  
  sought <- df[[seek_var]] == 1
  received_if_sought <- df[[rcv_var]][sought] == 1
  
  mean(received_if_sought, na.rm = TRUE)
})

# Convert to data frame for display
success_df <- data.frame(
  FundingType = funding_types,
  SuccessRate = round(success_rates, 3)
)

# View the results
print(success_df)

##                                       FundingType SuccessRate
## FndRaise_LocGvtGrnt           FndRaise_LocGvtGrnt       0.810
## FndRaise_StateGvtGrnt       FndRaise_StateGvtGrnt       0.794
## FndRaise_FedGvtGrnt           FndRaise_FedGvtGrnt       0.653
## FndRaise_LocGvtCntrct       FndRaise_LocGvtCntrct       0.782
## FndRaise_StateGvtCntrct   FndRaise_StateGvtCntrct       0.784
## FndRaise_FedGvtCntrct       FndRaise_FedGvtCntrct       0.620
## FndRaise_PFGrnt                   FndRaise_PFGrnt       0.865
## FndRaise_CFGrnt                   FndRaise_CFGrnt       0.798
## FndRaise_DAF                         FndRaise_DAF       0.859
## FndRaise_Corp_Found_Grnt FndRaise_Corp_Found_Grnt       0.850
## FndRaise_UntdWy                   FndRaise_UntdWy       0.799
## FndRaise_CombFedCmpgn       FndRaise_CombFedCmpgn       0.559
## FndRaise_OthrGvngPrgrm     FndRaise_OthrGvngPrgrm       0.691

local gov grants - Weighted

We conducted a Rao & Scott-adjusted chi-squared test to evaluate whether the success rate of receiving local government grants differed across nonprofit sectors, among those that sought such funding. Using the year4wt weight to account for differences in response rates by size, sector, and region, the test revealed a statistically significant association between sector and funding success (F = 2.78, df = 6.90, p = 0.0072). This suggests that some nonprofit sectors are more or less likely to receive local government grants after seeking them.

library(dplyr)
library(ggplot2)
library(survey)

## Warning: package 'survey' was built under R version 4.4.3

## Loading required package: grid

## Loading required package: Matrix

## Loading required package: survival

## 
## Attaching package: 'survey'

## The following object is masked from 'package:graphics':
## 
##     dotchart

# Step 1: Add sector groupings
data04_cleaned <- data04 |>
  mutate(
    sector_group = case_when(
      ntee1 == "A" ~ "I. Arts, Culture, Humanities",
      ntee1 == "B" ~ "II. Education",
      ntee1 %in% c("C", "D") ~ "III. Environment & Animals",
      ntee1 %in% c("E", "F", "G", "H") ~ "IV. Health",
      ntee1 %in% c("I", "J", "K", "L", "M", "N", "O", "P") ~ "V. Human Services",
      ntee1 == "Q" ~ "VI. International",
      ntee1 %in% c("R", "S", "T", "U", "V", "W") ~ "VII. Public/Societal Benefit",
      ntee1 == "X" ~ "VIII. Religion Related",
      ntee1 == "Y" ~ "IX. Mutual/Membership Benefit",
      ntee1 == "Z" ~ "X. Unknown/Unclassified",
      TRUE ~ "Other"
    )
  )

# Step 2: Filter to those who sought local government grants
data_sought <- data04_cleaned |>
  filter(FndRaise_LocGvtGrnt_Seek == 1) |>
  mutate(
    FndRaise_LocGvtGrnt_Rcv = factor(FndRaise_LocGvtGrnt_Rcv, levels = c(0, 1)),
    sector_group = factor(sector_group)
  )

# Step 3: Set up weighted survey design
design <- svydesign(ids = ~1, weights = ~year4wt, data = data_sought)

# Step 4: Run weighted chi-square test
chi_result <- svychisq(~ sector_group + FndRaise_LocGvtGrnt_Rcv, design = design)

# Step 5: Print results
print(chi_result)

## 
##  Pearson's X^2: Rao & Scott adjustment
## 
## data:  svychisq(~sector_group + FndRaise_LocGvtGrnt_Rcv, design = design)
## F = 2.7811, ndf = 6.9013, ddf = 12235.9374, p-value = 0.007168

# Step 6: Plot success rates (still unweighted for visualization)
success_by_sector <- data_sought |>
  group_by(sector_group) |>
  summarise(
    total_sought = n(),
    total_received = sum(FndRaise_LocGvtGrnt_Rcv == 1, na.rm = TRUE),
    success_rate = round(100 * total_received / total_sought, 1)
  ) |>
  arrange(desc(success_rate))

ggplot(success_by_sector, aes(x = reorder(sector_group, success_rate), y = success_rate)) +
  geom_col(fill = "steelblue") +
  geom_text(aes(label = paste0(success_rate, "%")), hjust = -0.1, size = 3.5) +
  coord_flip() +
  labs(
    title = "Success Rate of Receiving Local Government Grants (Among Seekers)",
    x = "Nonprofit Sector",
    y = "Success Rate (%)"
  ) +
  theme_minimal(base_size = 12) +
  ylim(0, 110)

seeking and recieving state gov grant- Not weighted

To assess whether the likelihood of receiving a state government grant differs by nonprofit sector among those that sought funding, a chi-square test of independence was conducted. The test revealed a statistically significant association between sector and grant receipt (p = 0.0004).

This indicates that nonprofit sectors are not equally likely to receive state government funding after seeking it. As shown in the accompanying bar chart, organizations in the Arts, Culture, and Humanities (83.2%) and Human Services (81.7%) sectors had the highest success rates, while Religion Related (50.0%) and International (53.8%) organizations had the lowest. These differences suggest that sector type may influence access to public funding, even after controlling for application effort.

data04_cleaned <- data04 |>
  mutate(
    sector_group = case_when(
      ntee1 == "A" ~ "I. Arts, Culture, Humanities",
      ntee1 == "B" ~ "II. Education",
      ntee1 %in% c("C", "D") ~ "III. Environment & Animals",
      ntee1 %in% c("E", "F", "G", "H") ~ "IV. Health",
      ntee1 %in% c("I", "J", "K", "L", "M", "N", "O", "P") ~ "V. Human Services",
      ntee1 == "Q" ~ "VI. International",
      ntee1 %in% c("R", "S", "T", "U", "V", "W") ~ "VII. Public/Societal Benefit",
      ntee1 == "X" ~ "VIII. Religion Related",
      ntee1 == "Y" ~ "IX. Mutual/Membership Benefit",
      ntee1 == "Z" ~ "X. Unknown/Unclassified",
      TRUE ~ "Other"
    )
  )

# Filter to only those who sought a local government grant
data_sought <- data04_cleaned |>
  filter(FndRaise_StateGvtGrnt_Seek == 1)

# Create contingency table for receiving by sector
contingency_table <- table(data_sought$sector_group, data_sought$FndRaise_StateGvtGrnt_Rcv)

# Run chi-square test
chi_squared_result <- chisq.test(contingency_table)

## Warning in chisq.test(contingency_table): Chi-squared approximation may be
## incorrect

# Output
print(contingency_table)

##                               
##                                  0   1
##   I. Arts, Culture, Humanities  82 405
##   II. Education                 25  55
##   III. Environment & Animals    35  93
##   IV. Health                    29 101
##   V. Human Services            123 550
##   VI. International              6   7
##   VII. Public/Societal Benefit  40 104
##   VIII. Religion Related         1   1

print(chi_squared_result)

## 
##  Pearson's Chi-squared test
## 
## data:  contingency_table
## X-squared = 26.576, df = 7, p-value = 0.0003972

library(dplyr)
library(ggplot2)

# Filter to organizations that sought local government grants
data_sought <- data04_cleaned |>
  filter(FndRaise_StateGvtGrnt_Seek == 1)

# Calculate success rates per sector
success_by_sector <- data_sought |>
  group_by(sector_group) |>
  summarise(
    total_sought = n(),
    total_received = sum(FndRaise_StateGvtGrnt_Rcv == 1, na.rm = TRUE),
    success_rate = round(100 * total_received / total_sought, 1)
  ) |>
  arrange(desc(success_rate))

# Plot
ggplot(success_by_sector, aes(x = reorder(sector_group, success_rate), y = success_rate)) +
  geom_col(fill = "steelblue") +
  geom_text(aes(label = paste0(success_rate, "%")), hjust = -0.1, size = 3.5) +
  coord_flip() +
  labs(
    title = "Success Rate of Receiving State Government Grants (Among Seekers)",
    x = "Nonprofit Sector",
    y = "Success Rate (%)"
  ) +
  theme_minimal(base_size = 12) +
  ylim(0, 110)

#weighted 
library(dplyr)
library(ggplot2)
library(survey)

# Step 1: Add sector groupings
data04_cleaned <- data04 |>
  mutate(
    sector_group = case_when(
      ntee1 == "A" ~ "I. Arts, Culture, Humanities",
      ntee1 == "B" ~ "II. Education",
      ntee1 %in% c("C", "D") ~ "III. Environment & Animals",
      ntee1 %in% c("E", "F", "G", "H") ~ "IV. Health",
      ntee1 %in% c("I", "J", "K", "L", "M", "N", "O", "P") ~ "V. Human Services",
      ntee1 == "Q" ~ "VI. International",
      ntee1 %in% c("R", "S", "T", "U", "V", "W") ~ "VII. Public/Societal Benefit",
      ntee1 == "X" ~ "VIII. Religion Related",
      ntee1 == "Y" ~ "IX. Mutual/Membership Benefit",
      ntee1 == "Z" ~ "X. Unknown/Unclassified",
      TRUE ~ "Other"
    )
  )

# Step 2: Filter to only those who sought state government grants
data_sought <- data04_cleaned |>
  filter(FndRaise_StateGvtGrnt_Seek == 1) |>
  mutate(
    FndRaise_StateGvtGrnt_Rcv = factor(FndRaise_StateGvtGrnt_Rcv, levels = c(0, 1)),
    sector_group = factor(sector_group)
  )

# Step 3: Define survey design using weights
design <- svydesign(
  ids = ~1,
  weights = ~year4wt,
  data = data_sought
)

# Step 4: Weighted chi-squared test
chi_result <- svychisq(~sector_group + FndRaise_StateGvtGrnt_Rcv, design = design)

# Step 5: Print test results
print(chi_result)

## 
##  Pearson's X^2: Rao & Scott adjustment
## 
## data:  svychisq(~sector_group + FndRaise_StateGvtGrnt_Rcv, design = design)
## F = 3.5677, ndf = 6.9425, ddf = 11496.7938, p-value = 0.0008056

# Step 6: Weighted success rate plot (optional but unweighted here for simplicity)
success_by_sector <- data_sought |>
  group_by(sector_group) |>
  summarise(
    total_sought = n(),
    total_received = sum(FndRaise_StateGvtGrnt_Rcv == 1, na.rm = TRUE),
    success_rate = round(100 * total_received / total_sought, 1)
  ) |>
  arrange(desc(success_rate))

ggplot(success_by_sector, aes(x = reorder(sector_group, success_rate), y = success_rate)) +
  geom_col(fill = "steelblue") +
  geom_text(aes(label = paste0(success_rate, "%")), hjust = -0.1, size = 3.5) +
  coord_flip() +
  labs(
    title = "Success Rate of Receiving State Government Grants (Among Seekers)",
    x = "Nonprofit Sector",
    y = "Success Rate (%)"
  ) +
  theme_minimal(base_size = 12) +
  ylim(0, 110)

seeking and recieving federal gov grant

• Not weighted Among nonprofits that sought federal government grants, success rates varied by sector. For example, organizations in Public/Societal Benefit and Human Services sectors had the highest success rates (72.2% and 71.3%, respectively), while International and Health sectors had the lowest (44.4% and 56.7%).

These differences are statistically significant (p = 0.00039), suggesting that sector plays a role in federal funding outcomes even among those who applied.

• Weighted A weighted chi-squared test using the Rao & Scott adjustment was conducted to examine whether the likelihood of receiving federal government grants differed across nonprofit sectors, among organizations that sought such funding. Accounting for sample weights (year4wt), the association was statistically significant (F = 3.72, adjusted df = 6.89, p = 0.00054). This suggests that some sectors had a significantly higher or lower success rate than others in securing federal grants after seeking them.

# Create sector groupings
data04_cleaned <- data04 |>
  mutate(
    sector_group = case_when(
      ntee1 == "A" ~ "I. Arts, Culture, Humanities",
      ntee1 == "B" ~ "II. Education",
      ntee1 %in% c("C", "D") ~ "III. Environment & Animals",
      ntee1 %in% c("E", "F", "G", "H") ~ "IV. Health",
      ntee1 %in% c("I", "J", "K", "L", "M", "N", "O", "P") ~ "V. Human Services",
      ntee1 == "Q" ~ "VI. International",
      ntee1 %in% c("R", "S", "T", "U", "V", "W") ~ "VII. Public/Societal Benefit",
      ntee1 == "X" ~ "VIII. Religion Related",
      ntee1 == "Y" ~ "IX. Mutual/Membership Benefit",
      ntee1 == "Z" ~ "X. Unknown/Unclassified",
      TRUE ~ "Other"
    )
  )

# Filter to those who sought federal grants (not those who received)
data_sought <- data04_cleaned |>
  filter(FndRaise_FedGvtGrnt_Seek == 1)

#Ensure 'received' column has both 0s and 1s for Chi-square to work
data_sought$FndRaise_FedGvtGrnt_Rcv <- factor(
  data_sought$FndRaise_FedGvtGrnt_Rcv, levels = c(0, 1)
)

#not weighted

# Build contingency table
contingency_table <- table(data_sought$sector_group, data_sought$FndRaise_FedGvtGrnt_Rcv)

# Run chi-square test
chi_squared_result <- chisq.test(contingency_table)

## Warning in chisq.test(contingency_table): Chi-squared approximation may be
## incorrect

# Output
print(contingency_table)

##                               
##                                  0   1
##   I. Arts, Culture, Humanities 118 161
##   II. Education                 17  29
##   III. Environment & Animals    38  62
##   IV. Health                    42  55
##   V. Human Services            149 370
##   VI. International             15  12
##   VII. Public/Societal Benefit  32  83
##   VIII. Religion Related         1   2

print(chi_squared_result)

## 
##  Pearson's Chi-squared test
## 
## data:  contingency_table
## X-squared = 26.639, df = 7, p-value = 0.0003869

#weighted

library(survey)

# Step 1: Create survey design object using year4wt
design <- svydesign(ids = ~1, data = data_sought, weights = ~year4wt)

# Step 2: Run weighted chi-squared test using Rao & Scott adjustment
svy_result <- svychisq(~ sector_group + FndRaise_FedGvtGrnt_Rcv, design = design)

# Step 3: Output result
print(svy_result)

## 
##  Pearson's X^2: Rao & Scott adjustment
## 
## data:  svychisq(~sector_group + FndRaise_FedGvtGrnt_Rcv, design = design)
## F = 3.7229, ndf = 6.8941, ddf = 8169.4502, p-value = 0.0005396

# Calculate success rate per sector
library(dplyr)
library(ggplot2)

success_by_sector <- data_sought |>
  group_by(sector_group) |>
  summarise(
    total_sought = n(),
    total_received = sum(FndRaise_FedGvtGrnt_Rcv == 1, na.rm = TRUE),
    success_rate = round(100 * total_received / total_sought, 1)
  ) |>
  arrange(desc(success_rate))

# Plot success rate
ggplot(success_by_sector, aes(x = reorder(sector_group, success_rate), y = success_rate)) +
  geom_col(fill = "steelblue") +
  geom_text(aes(label = paste0(success_rate, "%")), hjust = -0.1, size = 3.5) +
  coord_flip() +
  labs(
    title = "Success Rate of Receiving Federal Government Grants (Among Seekers)",
    x = "Nonprofit Sector",
    y = "Success Rate (%)"
  ) +
  theme_minimal(base_size = 12) +
  ylim(0, 110)

library(tidyr)

## 
## Attaching package: 'tidyr'

## The following objects are masked from 'package:Matrix':
## 
##     expand, pack, unpack

library(dplyr)

# Define relevant columns
grant_cols <- c("LocGvtGrnt", "StateGvtGrnt", "FedGvtGrnt")

# Create long-format data for modeling
long_data <- data04_cleaned |>
  pivot_longer(
    cols = starts_with("FndRaise_"),
    names_to = c("grant_type", ".value"),
    names_pattern = "FndRaise_(.*)_(Seek|Rcv)"
  ) |>
  filter(Seek == 1) |>  # Only include rows where the org applied
  rename(received = Rcv)

model <- glm(received ~ grant_type * sector_group,
             data = long_data,
             family = "binomial")

summary(model)

## 
## Call:
## glm(formula = received ~ grant_type * sector_group, family = "binomial", 
##     data = long_data)
## 
## Coefficients: (6 not defined because of singularities)
##                                                                      Estimate
## (Intercept)                                                          1.450456
## grant_typeCombFedCmpgn                                              -2.366747
## grant_typeCorp_Found_Grnt                                            0.264930
## grant_typeDAF                                                        0.915308
## grant_typeFedGvtCntrct                                              -1.768910
## grant_typeFedGvtGrnt                                                -1.139737
## grant_typeLocGvtCntrct                                              -0.469627
## grant_typeLocGvtGrnt                                                 0.375041
## grant_typeOthrGvngPrgrm                                             -0.351844
## grant_typePFGrnt                                                     0.353425
## grant_typeStateGvtCntrct                                            -0.757309
## grant_typeStateGvtGrnt                                               0.146712
## grant_typeUntdWy                                                    -0.197693
## sector_groupII. Education                                           -0.489994
## sector_groupIII. Environment & Animals                              -0.046035
## sector_groupIV. Health                                              -0.332976
## sector_groupV. Human Services                                        0.008942
## sector_groupVI. International                                       -1.067464
## sector_groupVII. Public/Societal Benefit                             0.046652
## sector_groupVIII. Religion Related                                  -1.044991
## grant_typeCombFedCmpgn:sector_groupII. Education                    14.972352
## grant_typeCorp_Found_Grnt:sector_groupII. Education                  0.039205
## grant_typeDAF:sector_groupII. Education                             -0.489475
## grant_typeFedGvtCntrct:sector_groupII. Education                    14.374515
## grant_typeFedGvtGrnt:sector_groupII. Education                       0.713357
## grant_typeLocGvtCntrct:sector_groupII. Education                     1.501595
## grant_typeLocGvtGrnt:sector_groupII. Education                      -0.584087
## grant_typeOthrGvngPrgrm:sector_groupII. Education                    1.588607
## grant_typePFGrnt:sector_groupII. Education                           0.304210
## grant_typeStateGvtCntrct:sector_groupII. Education                   2.630061
## grant_typeStateGvtGrnt:sector_groupII. Education                    -0.318716
## grant_typeUntdWy:sector_groupII. Education                           0.623526
## grant_typeCombFedCmpgn:sector_groupIII. Environment & Animals        2.261608
## grant_typeCorp_Found_Grnt:sector_groupIII. Environment & Animals    -0.001074
## grant_typeDAF:sector_groupIII. Environment & Animals                -0.373819
## grant_typeFedGvtCntrct:sector_groupIII. Environment & Animals        1.057635
## grant_typeFedGvtGrnt:sector_groupIII. Environment & Animals          0.224863
## grant_typeLocGvtCntrct:sector_groupIII. Environment & Animals        0.832867
## grant_typeLocGvtGrnt:sector_groupIII. Environment & Animals         -0.575490
## grant_typeOthrGvngPrgrm:sector_groupIII. Environment & Animals      -0.851907
## grant_typePFGrnt:sector_groupIII. Environment & Animals              0.372687
## grant_typeStateGvtCntrct:sector_groupIII. Environment & Animals      0.451500
## grant_typeStateGvtGrnt:sector_groupIII. Environment & Animals       -0.573882
## grant_typeUntdWy:sector_groupIII. Environment & Animals              0.061783
## grant_typeCombFedCmpgn:sector_groupIV. Health                        0.892591
## grant_typeCorp_Found_Grnt:sector_groupIV. Health                    -0.054224
## grant_typeDAF:sector_groupIV. Health                                -0.566451
## grant_typeFedGvtCntrct:sector_groupIV. Health                        1.344576
## grant_typeFedGvtGrnt:sector_groupIV. Health                          0.291919
## grant_typeLocGvtCntrct:sector_groupIV. Health                        0.393600
## grant_typeLocGvtGrnt:sector_groupIV. Health                          0.041408
## grant_typeOthrGvngPrgrm:sector_groupIV. Health                      -0.330319
## grant_typePFGrnt:sector_groupIV. Health                              0.036533
## grant_typeStateGvtCntrct:sector_groupIV. Health                      1.056894
## grant_typeStateGvtGrnt:sector_groupIV. Health                       -0.016368
## grant_typeUntdWy:sector_groupIV. Health                              0.160133
## grant_typeCombFedCmpgn:sector_groupV. Human Services                 1.223686
## grant_typeCorp_Found_Grnt:sector_groupV. Human Services              0.145104
## grant_typeDAF:sector_groupV. Human Services                         -0.635912
## grant_typeFedGvtCntrct:sector_groupV. Human Services                 0.846313
## grant_typeFedGvtGrnt:sector_groupV. Human Services                   0.589895
## grant_typeLocGvtCntrct:sector_groupV. Human Services                 0.195273
## grant_typeLocGvtGrnt:sector_groupV. Human Services                  -0.426851
## grant_typeOthrGvngPrgrm:sector_groupV. Human Services               -0.206768
## grant_typePFGrnt:sector_groupV. Human Services                       0.194088
## grant_typeStateGvtCntrct:sector_groupV. Human Services               0.580136
## grant_typeStateGvtGrnt:sector_groupV. Human Services                -0.108376
## grant_typeUntdWy:sector_groupV. Human Services                       0.143432
## grant_typeCombFedCmpgn:sector_groupVI. International                 2.389220
## grant_typeCorp_Found_Grnt:sector_groupVI. International              0.565100
## grant_typeDAF:sector_groupVI. International                          0.419352
## grant_typeFedGvtCntrct:sector_groupVI. International               -12.180149
## grant_typeFedGvtGrnt:sector_groupVI. International                   0.533601
## grant_typeLocGvtCntrct:sector_groupVI. International                 1.696073
## grant_typeLocGvtGrnt:sector_groupVI. International                  -0.064886
## grant_typeOthrGvngPrgrm:sector_groupVI. International                0.528468
## grant_typePFGrnt:sector_groupVI. International                       0.430018
## grant_typeStateGvtCntrct:sector_groupVI. International                     NA
## grant_typeStateGvtGrnt:sector_groupVI. International                -0.375553
## grant_typeUntdWy:sector_groupVI. International                      -0.590764
## grant_typeCombFedCmpgn:sector_groupVII. Public/Societal Benefit     -0.111191
## grant_typeCorp_Found_Grnt:sector_groupVII. Public/Societal Benefit   0.258906
## grant_typeDAF:sector_groupVII. Public/Societal Benefit              -0.908339
## grant_typeFedGvtCntrct:sector_groupVII. Public/Societal Benefit      1.033941
## grant_typeFedGvtGrnt:sector_groupVII. Public/Societal Benefit        0.595733
## grant_typeLocGvtCntrct:sector_groupVII. Public/Societal Benefit      0.581956
## grant_typeLocGvtGrnt:sector_groupVII. Public/Societal Benefit       -0.510347
## grant_typeOthrGvngPrgrm:sector_groupVII. Public/Societal Benefit    -0.788590
## grant_typePFGrnt:sector_groupVII. Public/Societal Benefit           -0.084351
## grant_typeStateGvtCntrct:sector_groupVII. Public/Societal Benefit    0.908859
## grant_typeStateGvtGrnt:sector_groupVII. Public/Societal Benefit     -0.688309
## grant_typeUntdWy:sector_groupVII. Public/Societal Benefit            0.724966
## grant_typeCombFedCmpgn:sector_groupVIII. Religion Related                  NA
## grant_typeCorp_Found_Grnt:sector_groupVIII. Religion Related        12.895671
## grant_typeDAF:sector_groupVIII. Religion Related                    -0.222161
## grant_typeFedGvtCntrct:sector_groupVIII. Religion Related                  NA
## grant_typeFedGvtGrnt:sector_groupVIII. Religion Related              1.427419
## grant_typeLocGvtCntrct:sector_groupVIII. Religion Related                  NA
## grant_typeLocGvtGrnt:sector_groupVIII. Religion Related             -0.780506
## grant_typeOthrGvngPrgrm:sector_groupVIII. Religion Related                 NA
## grant_typePFGrnt:sector_groupVIII. Religion Related                  0.339723
## grant_typeStateGvtCntrct:sector_groupVIII. Religion Related                NA
## grant_typeStateGvtGrnt:sector_groupVIII. Religion Related           -0.552177
## grant_typeUntdWy:sector_groupVIII. Religion Related                 13.358295
##                                                                    Std. Error
## (Intercept)                                                          0.121955
## grant_typeCombFedCmpgn                                               0.845502
## grant_typeCorp_Found_Grnt                                            0.179512
## grant_typeDAF                                                        0.249866
## grant_typeFedGvtCntrct                                               0.480398
## grant_typeFedGvtGrnt                                                 0.171927
## grant_typeLocGvtCntrct                                               0.302096
## grant_typeLocGvtGrnt                                                 0.178742
## grant_typeOthrGvngPrgrm                                              0.426075
## grant_typePFGrnt                                                     0.170517
## grant_typeStateGvtCntrct                                             0.373996
## grant_typeStateGvtGrnt                                               0.171864
## grant_typeUntdWy                                                     0.349308
## sector_groupII. Education                                            0.243879
## sector_groupIII. Environment & Animals                               0.212724
## sector_groupIV. Health                                               0.229761
## sector_groupV. Human Services                                        0.147636
## sector_groupVI. International                                        0.356363
## sector_groupVII. Public/Societal Benefit                             0.230469
## sector_groupVIII. Religion Related                                   0.920981
## grant_typeCombFedCmpgn:sector_groupII. Education                   239.444740
## grant_typeCorp_Found_Grnt:sector_groupII. Education                  0.360915
## grant_typeDAF:sector_groupII. Education                              0.481702
## grant_typeFedGvtCntrct:sector_groupII. Education                   309.120228
## grant_typeFedGvtGrnt:sector_groupII. Education                       0.409230
## grant_typeLocGvtCntrct:sector_groupII. Education                     0.717394
## grant_typeLocGvtGrnt:sector_groupII. Education                       0.367995
## grant_typeOthrGvngPrgrm:sector_groupII. Education                    1.156397
## grant_typePFGrnt:sector_groupII. Education                           0.354653
## grant_typeStateGvtCntrct:sector_groupII. Education                   1.115034
## grant_typeStateGvtGrnt:sector_groupII. Education                     0.363762
## grant_typeUntdWy:sector_groupII. Education                           0.568216
## grant_typeCombFedCmpgn:sector_groupIII. Environment & Animals        1.081431
## grant_typeCorp_Found_Grnt:sector_groupIII. Environment & Animals     0.314038
## grant_typeDAF:sector_groupIII. Environment & Animals                 0.400048
## grant_typeFedGvtCntrct:sector_groupIII. Environment & Animals        0.689526
## grant_typeFedGvtGrnt:sector_groupIII. Environment & Animals          0.319972
## grant_typeLocGvtCntrct:sector_groupIII. Environment & Animals        0.537483
## grant_typeLocGvtGrnt:sector_groupIII. Environment & Animals          0.318937
## grant_typeOthrGvngPrgrm:sector_groupIII. Environment & Animals       0.643380
## grant_typePFGrnt:sector_groupIII. Environment & Animals              0.309102
## grant_typeStateGvtCntrct:sector_groupIII. Environment & Animals      0.580446
## grant_typeStateGvtGrnt:sector_groupIII. Environment & Animals        0.315023
## grant_typeUntdWy:sector_groupIII. Environment & Animals              0.542914
## grant_typeCombFedCmpgn:sector_groupIV. Health                        0.997821
## grant_typeCorp_Found_Grnt:sector_groupIV. Health                     0.333087
## grant_typeDAF:sector_groupIV. Health                                 0.427085
## grant_typeFedGvtCntrct:sector_groupIV. Health                        0.694971
## grant_typeFedGvtGrnt:sector_groupIV. Health                          0.330859
## grant_typeLocGvtCntrct:sector_groupIV. Health                        0.491858
## grant_typeLocGvtGrnt:sector_groupIV. Health                          0.353729
## grant_typeOthrGvngPrgrm:sector_groupIV. Health                       0.607610
## grant_typePFGrnt:sector_groupIV. Health                              0.322503
## grant_typeStateGvtCntrct:sector_groupIV. Health                      0.577142
## grant_typeStateGvtGrnt:sector_groupIV. Health                        0.334422
## grant_typeUntdWy:sector_groupIV. Health                              0.484104
## grant_typeCombFedCmpgn:sector_groupV. Human Services                 0.872927
## grant_typeCorp_Found_Grnt:sector_groupV. Human Services              0.219149
## grant_typeDAF:sector_groupV. Human Services                          0.288710
## grant_typeFedGvtCntrct:sector_groupV. Human Services                 0.528589
## grant_typeFedGvtGrnt:sector_groupV. Human Services                   0.214234
## grant_typeLocGvtCntrct:sector_groupV. Human Services                 0.354102
## grant_typeLocGvtGrnt:sector_groupV. Human Services                   0.217061
## grant_typeOthrGvngPrgrm:sector_groupV. Human Services                0.464227
## grant_typePFGrnt:sector_groupV. Human Services                       0.210868
## grant_typeStateGvtCntrct:sector_groupV. Human Services               0.420124
## grant_typeStateGvtGrnt:sector_groupV. Human Services                 0.215428
## grant_typeUntdWy:sector_groupV. Human Services                       0.377459
## grant_typeCombFedCmpgn:sector_groupVI. International                 1.288537
## grant_typeCorp_Found_Grnt:sector_groupVI. International              0.512135
## grant_typeDAF:sector_groupVI. International                          0.585707
## grant_typeFedGvtCntrct:sector_groupVI. International               309.120337
## grant_typeFedGvtGrnt:sector_groupVI. International                   0.540074
## grant_typeLocGvtCntrct:sector_groupVI. International                 1.184645
## grant_typeLocGvtGrnt:sector_groupVI. International                   0.666386
## grant_typeOthrGvngPrgrm:sector_groupVI. International                0.828564
## grant_typePFGrnt:sector_groupVI. International                       0.458500
## grant_typeStateGvtCntrct:sector_groupVI. International                     NA
## grant_typeStateGvtGrnt:sector_groupVI. International                 0.671701
## grant_typeUntdWy:sector_groupVI. International                       1.033185
## grant_typeCombFedCmpgn:sector_groupVII. Public/Societal Benefit      1.100659
## grant_typeCorp_Found_Grnt:sector_groupVII. Public/Societal Benefit   0.349208
## grant_typeDAF:sector_groupVII. Public/Societal Benefit               0.410582
## grant_typeFedGvtCntrct:sector_groupVII. Public/Societal Benefit      0.691772
## grant_typeFedGvtGrnt:sector_groupVII. Public/Societal Benefit        0.333317
## grant_typeLocGvtCntrct:sector_groupVII. Public/Societal Benefit      0.512678
## grant_typeLocGvtGrnt:sector_groupVII. Public/Societal Benefit        0.332737
## grant_typeOthrGvngPrgrm:sector_groupVII. Public/Societal Benefit     0.680176
## grant_typePFGrnt:sector_groupVII. Public/Societal Benefit            0.320630
## grant_typeStateGvtCntrct:sector_groupVII. Public/Societal Benefit    0.645428
## grant_typeStateGvtGrnt:sector_groupVII. Public/Societal Benefit      0.319993
## grant_typeUntdWy:sector_groupVII. Public/Societal Benefit            0.567436
## grant_typeCombFedCmpgn:sector_groupVIII. Religion Related                  NA
## grant_typeCorp_Found_Grnt:sector_groupVIII. Religion Related       239.444961
## grant_typeDAF:sector_groupVIII. Religion Related                     1.493017
## grant_typeFedGvtCntrct:sector_groupVIII. Religion Related                  NA
## grant_typeFedGvtGrnt:sector_groupVIII. Religion Related              1.537170
## grant_typeLocGvtCntrct:sector_groupVIII. Religion Related                  NA
## grant_typeLocGvtGrnt:sector_groupVIII. Religion Related              1.365753
## grant_typeOthrGvngPrgrm:sector_groupVIII. Religion Related                 NA
## grant_typePFGrnt:sector_groupVIII. Religion Related                  1.236558
## grant_typeStateGvtCntrct:sector_groupVIII. Religion Related                NA
## grant_typeStateGvtGrnt:sector_groupVIII. Religion Related            1.692002
## grant_typeUntdWy:sector_groupVIII. Religion Related                378.594130
##                                                                    z value
## (Intercept)                                                         11.893
## grant_typeCombFedCmpgn                                              -2.799
## grant_typeCorp_Found_Grnt                                            1.476
## grant_typeDAF                                                        3.663
## grant_typeFedGvtCntrct                                              -3.682
## grant_typeFedGvtGrnt                                                -6.629
## grant_typeLocGvtCntrct                                              -1.555
## grant_typeLocGvtGrnt                                                 2.098
## grant_typeOthrGvngPrgrm                                             -0.826
## grant_typePFGrnt                                                     2.073
## grant_typeStateGvtCntrct                                            -2.025
## grant_typeStateGvtGrnt                                               0.854
## grant_typeUntdWy                                                    -0.566
## sector_groupII. Education                                           -2.009
## sector_groupIII. Environment & Animals                              -0.216
## sector_groupIV. Health                                              -1.449
## sector_groupV. Human Services                                        0.061
## sector_groupVI. International                                       -2.995
## sector_groupVII. Public/Societal Benefit                             0.202
## sector_groupVIII. Religion Related                                  -1.135
## grant_typeCombFedCmpgn:sector_groupII. Education                     0.063
## grant_typeCorp_Found_Grnt:sector_groupII. Education                  0.109
## grant_typeDAF:sector_groupII. Education                             -1.016
## grant_typeFedGvtCntrct:sector_groupII. Education                     0.047
## grant_typeFedGvtGrnt:sector_groupII. Education                       1.743
## grant_typeLocGvtCntrct:sector_groupII. Education                     2.093
## grant_typeLocGvtGrnt:sector_groupII. Education                      -1.587
## grant_typeOthrGvngPrgrm:sector_groupII. Education                    1.374
## grant_typePFGrnt:sector_groupII. Education                           0.858
## grant_typeStateGvtCntrct:sector_groupII. Education                   2.359
## grant_typeStateGvtGrnt:sector_groupII. Education                    -0.876
## grant_typeUntdWy:sector_groupII. Education                           1.097
## grant_typeCombFedCmpgn:sector_groupIII. Environment & Animals        2.091
## grant_typeCorp_Found_Grnt:sector_groupIII. Environment & Animals    -0.003
## grant_typeDAF:sector_groupIII. Environment & Animals                -0.934
## grant_typeFedGvtCntrct:sector_groupIII. Environment & Animals        1.534
## grant_typeFedGvtGrnt:sector_groupIII. Environment & Animals          0.703
## grant_typeLocGvtCntrct:sector_groupIII. Environment & Animals        1.550
## grant_typeLocGvtGrnt:sector_groupIII. Environment & Animals         -1.804
## grant_typeOthrGvngPrgrm:sector_groupIII. Environment & Animals      -1.324
## grant_typePFGrnt:sector_groupIII. Environment & Animals              1.206
## grant_typeStateGvtCntrct:sector_groupIII. Environment & Animals      0.778
## grant_typeStateGvtGrnt:sector_groupIII. Environment & Animals       -1.822
## grant_typeUntdWy:sector_groupIII. Environment & Animals              0.114
## grant_typeCombFedCmpgn:sector_groupIV. Health                        0.895
## grant_typeCorp_Found_Grnt:sector_groupIV. Health                    -0.163
## grant_typeDAF:sector_groupIV. Health                                -1.326
## grant_typeFedGvtCntrct:sector_groupIV. Health                        1.935
## grant_typeFedGvtGrnt:sector_groupIV. Health                          0.882
## grant_typeLocGvtCntrct:sector_groupIV. Health                        0.800
## grant_typeLocGvtGrnt:sector_groupIV. Health                          0.117
## grant_typeOthrGvngPrgrm:sector_groupIV. Health                      -0.544
## grant_typePFGrnt:sector_groupIV. Health                              0.113
## grant_typeStateGvtCntrct:sector_groupIV. Health                      1.831
## grant_typeStateGvtGrnt:sector_groupIV. Health                       -0.049
## grant_typeUntdWy:sector_groupIV. Health                              0.331
## grant_typeCombFedCmpgn:sector_groupV. Human Services                 1.402
## grant_typeCorp_Found_Grnt:sector_groupV. Human Services              0.662
## grant_typeDAF:sector_groupV. Human Services                         -2.203
## grant_typeFedGvtCntrct:sector_groupV. Human Services                 1.601
## grant_typeFedGvtGrnt:sector_groupV. Human Services                   2.754
## grant_typeLocGvtCntrct:sector_groupV. Human Services                 0.551
## grant_typeLocGvtGrnt:sector_groupV. Human Services                  -1.967
## grant_typeOthrGvngPrgrm:sector_groupV. Human Services               -0.445
## grant_typePFGrnt:sector_groupV. Human Services                       0.920
## grant_typeStateGvtCntrct:sector_groupV. Human Services               1.381
## grant_typeStateGvtGrnt:sector_groupV. Human Services                -0.503
## grant_typeUntdWy:sector_groupV. Human Services                       0.380
## grant_typeCombFedCmpgn:sector_groupVI. International                 1.854
## grant_typeCorp_Found_Grnt:sector_groupVI. International              1.103
## grant_typeDAF:sector_groupVI. International                          0.716
## grant_typeFedGvtCntrct:sector_groupVI. International                -0.039
## grant_typeFedGvtGrnt:sector_groupVI. International                   0.988
## grant_typeLocGvtCntrct:sector_groupVI. International                 1.432
## grant_typeLocGvtGrnt:sector_groupVI. International                  -0.097
## grant_typeOthrGvngPrgrm:sector_groupVI. International                0.638
## grant_typePFGrnt:sector_groupVI. International                       0.938
## grant_typeStateGvtCntrct:sector_groupVI. International                  NA
## grant_typeStateGvtGrnt:sector_groupVI. International                -0.559
## grant_typeUntdWy:sector_groupVI. International                      -0.572
## grant_typeCombFedCmpgn:sector_groupVII. Public/Societal Benefit     -0.101
## grant_typeCorp_Found_Grnt:sector_groupVII. Public/Societal Benefit   0.741
## grant_typeDAF:sector_groupVII. Public/Societal Benefit              -2.212
## grant_typeFedGvtCntrct:sector_groupVII. Public/Societal Benefit      1.495
## grant_typeFedGvtGrnt:sector_groupVII. Public/Societal Benefit        1.787
## grant_typeLocGvtCntrct:sector_groupVII. Public/Societal Benefit      1.135
## grant_typeLocGvtGrnt:sector_groupVII. Public/Societal Benefit       -1.534
## grant_typeOthrGvngPrgrm:sector_groupVII. Public/Societal Benefit    -1.159
## grant_typePFGrnt:sector_groupVII. Public/Societal Benefit           -0.263
## grant_typeStateGvtCntrct:sector_groupVII. Public/Societal Benefit    1.408
## grant_typeStateGvtGrnt:sector_groupVII. Public/Societal Benefit     -2.151
## grant_typeUntdWy:sector_groupVII. Public/Societal Benefit            1.278
## grant_typeCombFedCmpgn:sector_groupVIII. Religion Related               NA
## grant_typeCorp_Found_Grnt:sector_groupVIII. Religion Related         0.054
## grant_typeDAF:sector_groupVIII. Religion Related                    -0.149
## grant_typeFedGvtCntrct:sector_groupVIII. Religion Related               NA
## grant_typeFedGvtGrnt:sector_groupVIII. Religion Related              0.929
## grant_typeLocGvtCntrct:sector_groupVIII. Religion Related               NA
## grant_typeLocGvtGrnt:sector_groupVIII. Religion Related             -0.571
## grant_typeOthrGvngPrgrm:sector_groupVIII. Religion Related              NA
## grant_typePFGrnt:sector_groupVIII. Religion Related                  0.275
## grant_typeStateGvtCntrct:sector_groupVIII. Religion Related             NA
## grant_typeStateGvtGrnt:sector_groupVIII. Religion Related           -0.326
## grant_typeUntdWy:sector_groupVIII. Religion Related                  0.035
##                                                                    Pr(>|z|)    
## (Intercept)                                                         < 2e-16 ***
## grant_typeCombFedCmpgn                                             0.005123 ** 
## grant_typeCorp_Found_Grnt                                          0.139987    
## grant_typeDAF                                                      0.000249 ***
## grant_typeFedGvtCntrct                                             0.000231 ***
## grant_typeFedGvtGrnt                                               3.38e-11 ***
## grant_typeLocGvtCntrct                                             0.120050    
## grant_typeLocGvtGrnt                                               0.035885 *  
## grant_typeOthrGvngPrgrm                                            0.408929    
## grant_typePFGrnt                                                   0.038204 *  
## grant_typeStateGvtCntrct                                           0.042876 *  
## grant_typeStateGvtGrnt                                             0.393300    
## grant_typeUntdWy                                                   0.571423    
## sector_groupII. Education                                          0.044519 *  
## sector_groupIII. Environment & Animals                             0.828672    
## sector_groupIV. Health                                             0.147275    
## sector_groupV. Human Services                                      0.951702    
## sector_groupVI. International                                      0.002740 ** 
## sector_groupVII. Public/Societal Benefit                           0.839586    
## sector_groupVIII. Religion Related                                 0.256522    
## grant_typeCombFedCmpgn:sector_groupII. Education                   0.950141    
## grant_typeCorp_Found_Grnt:sector_groupII. Education                0.913498    
## grant_typeDAF:sector_groupII. Education                            0.309564    
## grant_typeFedGvtCntrct:sector_groupII. Education                   0.962911    
## grant_typeFedGvtGrnt:sector_groupII. Education                     0.081304 .  
## grant_typeLocGvtCntrct:sector_groupII. Education                   0.036338 *  
## grant_typeLocGvtGrnt:sector_groupII. Education                     0.112464    
## grant_typeOthrGvngPrgrm:sector_groupII. Education                  0.169518    
## grant_typePFGrnt:sector_groupII. Education                         0.391022    
## grant_typeStateGvtCntrct:sector_groupII. Education                 0.018338 *  
## grant_typeStateGvtGrnt:sector_groupII. Education                   0.380940    
## grant_typeUntdWy:sector_groupII. Education                         0.272493    
## grant_typeCombFedCmpgn:sector_groupIII. Environment & Animals      0.036500 *  
## grant_typeCorp_Found_Grnt:sector_groupIII. Environment & Animals   0.997272    
## grant_typeDAF:sector_groupIII. Environment & Animals               0.350079    
## grant_typeFedGvtCntrct:sector_groupIII. Environment & Animals      0.125064    
## grant_typeFedGvtGrnt:sector_groupIII. Environment & Animals        0.482206    
## grant_typeLocGvtCntrct:sector_groupIII. Environment & Animals      0.121245    
## grant_typeLocGvtGrnt:sector_groupIII. Environment & Animals        0.071168 .  
## grant_typeOthrGvngPrgrm:sector_groupIII. Environment & Animals     0.185466    
## grant_typePFGrnt:sector_groupIII. Environment & Animals            0.227930    
## grant_typeStateGvtCntrct:sector_groupIII. Environment & Animals    0.436658    
## grant_typeStateGvtGrnt:sector_groupIII. Environment & Animals      0.068499 .  
## grant_typeUntdWy:sector_groupIII. Environment & Animals            0.909397    
## grant_typeCombFedCmpgn:sector_groupIV. Health                      0.371033    
## grant_typeCorp_Found_Grnt:sector_groupIV. Health                   0.870681    
## grant_typeDAF:sector_groupIV. Health                               0.184734    
## grant_typeFedGvtCntrct:sector_groupIV. Health                      0.053024 .  
## grant_typeFedGvtGrnt:sector_groupIV. Health                        0.377610    
## grant_typeLocGvtCntrct:sector_groupIV. Health                      0.423577    
## grant_typeLocGvtGrnt:sector_groupIV. Health                        0.906811    
## grant_typeOthrGvngPrgrm:sector_groupIV. Health                     0.586692    
## grant_typePFGrnt:sector_groupIV. Health                            0.909808    
## grant_typeStateGvtCntrct:sector_groupIV. Health                    0.067063 .  
## grant_typeStateGvtGrnt:sector_groupIV. Health                      0.960965    
## grant_typeUntdWy:sector_groupIV. Health                            0.740809    
## grant_typeCombFedCmpgn:sector_groupV. Human Services               0.160969    
## grant_typeCorp_Found_Grnt:sector_groupV. Human Services            0.507893    
## grant_typeDAF:sector_groupV. Human Services                        0.027623 *  
## grant_typeFedGvtCntrct:sector_groupV. Human Services               0.109359    
## grant_typeFedGvtGrnt:sector_groupV. Human Services                 0.005896 ** 
## grant_typeLocGvtCntrct:sector_groupV. Human Services               0.581318    
## grant_typeLocGvtGrnt:sector_groupV. Human Services                 0.049240 *  
## grant_typeOthrGvngPrgrm:sector_groupV. Human Services              0.656028    
## grant_typePFGrnt:sector_groupV. Human Services                     0.357352    
## grant_typeStateGvtCntrct:sector_groupV. Human Services             0.167319    
## grant_typeStateGvtGrnt:sector_groupV. Human Services               0.614912    
## grant_typeUntdWy:sector_groupV. Human Services                     0.703950    
## grant_typeCombFedCmpgn:sector_groupVI. International               0.063709 .  
## grant_typeCorp_Found_Grnt:sector_groupVI. International            0.269844    
## grant_typeDAF:sector_groupVI. International                        0.474007    
## grant_typeFedGvtCntrct:sector_groupVI. International               0.968569    
## grant_typeFedGvtGrnt:sector_groupVI. International                 0.323146    
## grant_typeLocGvtCntrct:sector_groupVI. International               0.152226    
## grant_typeLocGvtGrnt:sector_groupVI. International                 0.922432    
## grant_typeOthrGvngPrgrm:sector_groupVI. International              0.523596    
## grant_typePFGrnt:sector_groupVI. International                     0.348306    
## grant_typeStateGvtCntrct:sector_groupVI. International                   NA    
## grant_typeStateGvtGrnt:sector_groupVI. International               0.576088    
## grant_typeUntdWy:sector_groupVI. International                     0.567465    
## grant_typeCombFedCmpgn:sector_groupVII. Public/Societal Benefit    0.919533    
## grant_typeCorp_Found_Grnt:sector_groupVII. Public/Societal Benefit 0.458444    
## grant_typeDAF:sector_groupVII. Public/Societal Benefit             0.026944 *  
## grant_typeFedGvtCntrct:sector_groupVII. Public/Societal Benefit    0.135012    
## grant_typeFedGvtGrnt:sector_groupVII. Public/Societal Benefit      0.073891 .  
## grant_typeLocGvtCntrct:sector_groupVII. Public/Societal Benefit    0.256320    
## grant_typeLocGvtGrnt:sector_groupVII. Public/Societal Benefit      0.125083    
## grant_typeOthrGvngPrgrm:sector_groupVII. Public/Societal Benefit   0.246297    
## grant_typePFGrnt:sector_groupVII. Public/Societal Benefit          0.792491    
## grant_typeStateGvtCntrct:sector_groupVII. Public/Societal Benefit  0.159087    
## grant_typeStateGvtGrnt:sector_groupVII. Public/Societal Benefit    0.031475 *  
## grant_typeUntdWy:sector_groupVII. Public/Societal Benefit          0.201384    
## grant_typeCombFedCmpgn:sector_groupVIII. Religion Related                NA    
## grant_typeCorp_Found_Grnt:sector_groupVIII. Religion Related       0.957049    
## grant_typeDAF:sector_groupVIII. Religion Related                   0.881712    
## grant_typeFedGvtCntrct:sector_groupVIII. Religion Related                NA    
## grant_typeFedGvtGrnt:sector_groupVIII. Religion Related            0.353096    
## grant_typeLocGvtCntrct:sector_groupVIII. Religion Related                NA    
## grant_typeLocGvtGrnt:sector_groupVIII. Religion Related            0.567671    
## grant_typeOthrGvngPrgrm:sector_groupVIII. Religion Related               NA    
## grant_typePFGrnt:sector_groupVIII. Religion Related                0.783522    
## grant_typeStateGvtCntrct:sector_groupVIII. Religion Related              NA    
## grant_typeStateGvtGrnt:sector_groupVIII. Religion Related          0.744163    
## grant_typeUntdWy:sector_groupVIII. Religion Related                0.971853    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## (Dispersion parameter for binomial family taken to be 1)
## 
##     Null deviance: 14731  on 14881  degrees of freedom
## Residual deviance: 14156  on 14784  degrees of freedom
## AIC: 14352
## 
## Number of Fisher Scoring iterations: 12

model1 <- glm(received ~ grant_type + sector_group,
             data = long_data,
             family = "binomial")

summary(model1) 

## 
## Call:
## glm(formula = received ~ grant_type + sector_group, family = "binomial", 
##     data = long_data)
## 
## Coefficients:
##                                           Estimate Std. Error z value Pr(>|z|)
## (Intercept)                               1.423912   0.068922  20.660  < 2e-16
## grant_typeCombFedCmpgn                   -1.136218   0.168827  -6.730 1.70e-11
## grant_typeCorp_Found_Grnt                 0.367000   0.081999   4.476 7.62e-06
## grant_typeDAF                             0.452996   0.098587   4.595 4.33e-06
## grant_typeFedGvtCntrct                   -0.892351   0.159036  -5.611 2.01e-08
## grant_typeFedGvtGrnt                     -0.742049   0.082266  -9.020  < 2e-16
## grant_typeLocGvtCntrct                   -0.086346   0.127049  -0.680 0.496743
## grant_typeLocGvtGrnt                      0.066873   0.081906   0.816 0.414235
## grant_typeOthrGvngPrgrm                  -0.562124   0.137581  -4.086 4.39e-05
## grant_typePFGrnt                          0.498039   0.079262   6.283 3.31e-10
## grant_typeStateGvtCntrct                 -0.092401   0.140351  -0.658 0.510311
## grant_typeStateGvtGrnt                   -0.029567   0.082142  -0.360 0.718882
## grant_typeUntdWy                         -0.004084   0.107425  -0.038 0.969674
## sector_groupII. Education                -0.328253   0.100813  -3.256 0.001130
## sector_groupIII. Environment & Animals   -0.076819   0.083051  -0.925 0.354985
## sector_groupIV. Health                   -0.290530   0.084894  -3.422 0.000621
## sector_groupV. Human Services             0.035251   0.056641   0.622 0.533704
## sector_groupVI. International            -0.729563   0.137634  -5.301 1.15e-07
## sector_groupVII. Public/Societal Benefit -0.029306   0.085204  -0.344 0.730879
## sector_groupVIII. Religion Related       -0.586994   0.399439  -1.470 0.141685
##                                             
## (Intercept)                              ***
## grant_typeCombFedCmpgn                   ***
## grant_typeCorp_Found_Grnt                ***
## grant_typeDAF                            ***
## grant_typeFedGvtCntrct                   ***
## grant_typeFedGvtGrnt                     ***
## grant_typeLocGvtCntrct                      
## grant_typeLocGvtGrnt                        
## grant_typeOthrGvngPrgrm                  ***
## grant_typePFGrnt                         ***
## grant_typeStateGvtCntrct                    
## grant_typeStateGvtGrnt                      
## grant_typeUntdWy                            
## sector_groupII. Education                ** 
## sector_groupIII. Environment & Animals      
## sector_groupIV. Health                   ***
## sector_groupV. Human Services               
## sector_groupVI. International            ***
## sector_groupVII. Public/Societal Benefit    
## sector_groupVIII. Religion Related          
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## (Dispersion parameter for binomial family taken to be 1)
## 
##     Null deviance: 14731  on 14881  degrees of freedom
## Residual deviance: 14292  on 14862  degrees of freedom
## AIC: 14332
## 
## Number of Fisher Scoring iterations: 4

received ~ grant_type + sector_group

## received ~ grant_type + sector_group

Difference in p and f values for the three grant types

library(knitr)
library(dplyr)

tribble(
  ~`Grant Type`, ~`F Statistic`, ~`Degrees of Freedom`, ~`p-value`, ~`Significance`,
  "Local Government Grants", 2.78, "df = 6.90, 12,236", 0.0072, "p < 0.01",
  "State Government Grants", 3.57, "df = 6.94, 11,497", 0.00081, "p < 0.001",
  "Federal Government Grants", 3.72, "df = 6.89, 8,169", 0.00054, "p < 0.001"
) %>%
  kable(caption = "Summary of Weighted Chi-Squared Tests by Grant Type")

library(ggplot2)

# Create summary data frame
grant_data <- data.frame(
  Grant_Type = c("Local Government Grants", "State Government Grants", "Federal Government Grants"),
  F_Statistic = c(2.78, 3.57, 3.72),
  p_value = c(0.0072, 0.00081, 0.00054)
)

# Plot
ggplot(grant_data, aes(x = reorder(Grant_Type, F_Statistic), y = F_Statistic)) +
  geom_col(fill = "steelblue") +
  coord_flip() +
  geom_text(aes(label = paste0("F = ", F_Statistic, "\np = ", p_value)),
            hjust = -0.1, size = 3.5) +
  labs(
    title = "Rao & Scott-Adjusted Chi-Squared Test Results by Grant Type",
    x = "Grant Type",
    y = "F Statistic"
  ) +
  theme_minimal(base_size = 12) +
  ylim(0, 4.5)

# plotly 
library(dplyr)
library(tidyr)

# Grant types to loop through
grant_vars <- list(
  "Local" = c("FndRaise_LocGvtGrnt_Seek", "FndRaise_LocGvtGrnt_Rcv"),
  "State" = c("FndRaise_StateGvtGrnt_Seek", "FndRaise_StateGvtGrnt_Rcv"),
  "Federal" = c("FndRaise_FedGvtGrnt_Seek", "FndRaise_FedGvtGrnt_Rcv")
)

# Build success_by_sector_long
success_by_sector_long <- purrr::map_dfr(
  names(grant_vars),
  function(grant_type) {
    seek_var <- grant_vars[[grant_type]][1]
    rcv_var <- grant_vars[[grant_type]][2]

    data04_cleaned %>%
      filter(.data[[seek_var]] == 1) %>%
      group_by(sector_group) %>%
      summarise(
        grant_type = grant_type,
        total_sought = n(),
        total_received = sum(.data[[rcv_var]] == 1, na.rm = TRUE),
        success_rate = round(100 * total_received / total_sought, 1),
        .groups = "drop"
      )
  }
)

library(plotly)

## Warning: package 'plotly' was built under R version 4.4.3

## 
## Attaching package: 'plotly'

## The following object is masked from 'package:ggplot2':
## 
##     last_plot

## The following object is masked from 'package:stats':
## 
##     filter

## The following object is masked from 'package:graphics':
## 
##     layout

plot_ly(
  data = success_by_sector_long,
  x = ~success_rate,
  y = ~sector_group,
  color = ~grant_type,
  type = 'bar',
  orientation = 'h',
  text = ~paste0(
    "Grant Type: ", grant_type,
    "<br>Sector: ", sector_group,
    "<br>Success Rate: ", success_rate, "%",
    "<br>Total Sought: ", total_sought,
    "<br>Total Received: ", total_received
  ),
  hoverinfo = 'text'
) %>%
  layout(
    title = "Success Rates of Receiving Government Grants by Sector and Type",
    xaxis = list(title = "Success Rate (%)", range = c(0, 100)),
    yaxis = list(title = ""),
    barmode = 'group',
    margin = list(l = 150)
  )

library(dplyr)
library(tidyr)

# Grant types to loop through
grant_vars <- list(
  "Local" = c("FndRaise_LocGvtGrnt_Seek", "FndRaise_LocGvtGrnt_Rcv"),
  "State" = c("FndRaise_StateGvtGrnt_Seek", "FndRaise_StateGvtGrnt_Rcv"),
  "Federal" = c("FndRaise_FedGvtGrnt_Seek", "FndRaise_FedGvtGrnt_Rcv")
)

# Build success_by_sector_long
success_by_sector_long <- purrr::map_dfr(
  names(grant_vars),
  function(grant_type) {
    seek_var <- grant_vars[[grant_type]][1]
    rcv_var <- grant_vars[[grant_type]][2]

    data04_cleaned %>%
      filter(.data[[seek_var]] == 1) %>%
      group_by(sector_group) %>%
      summarise(
        grant_type = grant_type,
        total_sought = n(),
        total_received = sum(.data[[rcv_var]] == 1, na.rm = TRUE),
        success_rate = round(100 * total_received / total_sought, 1),
        .groups = "drop"
      )
  }
)


library(plotly)

plot_ly(
  data = success_by_sector_long,
  x = ~success_rate,
  y = ~sector_group,
  color = ~grant_type,
  type = 'bar',
  orientation = 'h',
  text = ~paste0(
    "Grant Type: ", grant_type,
    "<br>Sector: ", sector_group,
    "<br>Success Rate: ", success_rate, "%",
    "<br>Total Sought: ", total_sought,
    "<br>Total Received: ", total_received
  ),
  hoverinfo = 'text'
) %>%
  layout(
    title = "Success Rates of Receiving Government Grants by Sector and Type",
    xaxis = list(title = "Success Rate (%)", range = c(0, 100)),
    yaxis = list(title = ""),
    barmode = 'group',
    margin = list(l = 150)
  )

library(dplyr)
library(survey)
library(tidyr)
library(plotly)

# Set up list to collect results
weighted_results <- list()

# Define grant types and variables
grant_types <- list(
  "Local"   = c("FndRaise_LocGvtGrnt_Seek", "FndRaise_LocGvtGrnt_Rcv"),
  "State"   = c("FndRaise_StateGvtGrnt_Seek", "FndRaise_StateGvtGrnt_Rcv"),
  "Federal" = c("FndRaise_FedGvtGrnt_Seek", "FndRaise_FedGvtGrnt_Rcv")
)

# Loop through each grant type
for (type in names(grant_types)) {
  seek_var <- grant_types[[type]][1]
  rcv_var <- grant_types[[type]][2]

  temp_data <- data04_cleaned %>%
    filter(.data[[seek_var]] == 1) %>%
    mutate(
      received = .data[[rcv_var]],
      grant_type = type
    )

  # Survey design with weights
  design <- svydesign(ids = ~1, weights = ~year4wt, data = temp_data)

  # Get success rate per sector group
  summary <- svyby(
    ~received,
    ~sector_group,
    design,
    svymean,
    vartype = c("ci")
  ) %>%
    mutate(
      success_rate = round(received * 100, 1),
      grant_type = type,
      lower = round(ci_l * 100, 1),
      upper = round(ci_u * 100, 1)
    ) %>%
    select(sector_group, grant_type, success_rate, lower, upper)

  weighted_results[[type]] <- summary
}

# Combine all grant types
success_by_sector_long_weighted <- bind_rows(weighted_results)



plot_ly(
  data = success_by_sector_long_weighted,
  x = ~success_rate,
  y = ~sector_group,
  color = ~grant_type,
  type = 'bar',
  orientation = 'h',
  error_x = ~list(array = upper - success_rate),
  text = ~paste(
    "Sector: ", sector_group,
    "<br>Grant Type: ", grant_type,
    "<br>Success Rate: ", success_rate, "%",
    "<br>CI: [", lower, "% - ", upper, "%]"
  ),
  hoverinfo = 'text'
) %>%
  layout(
    title = "Weighted Success Rates of Receiving Government Grants by Sector and Type",
    xaxis = list(title = "Success Rate (%)", range = c(0, 100)),
    yaxis = list(title = ""),
    barmode = 'group',
    margin = list(l = 150)
  )